1
|
Dahu BM, Alaboud K, Nowbuth AA, Puckett HM, Scott GJ, Sheets LR. The Role of Remote Sensing and Geospatial Analysis for Understanding COVID-19 Population Severity: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4298. [PMID: 36901308 PMCID: PMC10002247 DOI: 10.3390/ijerph20054298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/30/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.
Collapse
Affiliation(s)
- Butros M. Dahu
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
| | - Khuder Alaboud
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- NextGen Biomedical Informatics Center, University of Missouri, Columbia, MO 65211, USA
| | - Avis Anya Nowbuth
- Pan African Organization for Health Education and Research (POHER), Manchester, MO 63011, USA
| | - Hunter M. Puckett
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
| | - Grant J. Scott
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Lincoln R. Sheets
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
- Department of Health Management and Informatics, University of Missouri, Columbia, MO 65211, USA
| |
Collapse
|
2
|
Yum S. The COVID-19 Response in North America. Disaster Med Public Health Prep 2022; 17:e320. [PMID: 36522684 DOI: 10.1017/dmp.2022.290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
In our Information Technology (IT) based societies, social media plays an important role in communications and social networks for COVID-19. This study explores social responses for COVID-19 in North America, which is the most severe continent affected by the COVID-19 pandemic. This study employs social network analysis for Twitter among the US, Canada, and Mexico. This study finds that the 3 countries show different characteristics of social networks for COVID-19. For example, the Prime Minister plays the second most important role in the Canadian networks, whereas the Presidents play the most significant role in them, in the US, and Mexico. WHO shows a pivotal effect on social networks of COVID-19 in Canada and the US, whereas it does not affect them in Mexico. Canadians are interested in COVID-19 apps, the American people criticize the president and administration as incompetent in terms of COVID-19, and the Mexican people search for COVID-19 cases and the pandemic in Mexico. This study shows that governments and disease experts should understand social networks and communications of social network services, to develop effective COVID-19 policies according to the characteristics of their country.
Collapse
Affiliation(s)
- Seungil Yum
- Design, Construction, and Planning, University of Florida, Gainesville, FL, USA
| |
Collapse
|
3
|
Chen Q, Zhu K, Liu X, Zhuang C, Huang X, Huang Y, Yao X, Quan J, Lin H, Huang S, Su Y, Wu T, Zhang J, Xia N. The Protection of Naturally Acquired Antibodies Against Subsequent SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis. Emerg Microbes Infect 2022; 11:793-803. [PMID: 35195494 PMCID: PMC8920404 DOI: 10.1080/22221751.2022.2046446] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The specific antibodies induced by SARS-CoV-2 infection may provide protection against a subsequent infection. However, the efficacy and duration of protection provided by naturally acquired immunity against subsequent SARS-CoV-2 infection remain controversial. We systematically searched for the literature describing COVID-19 reinfection published before 07 February 2022. The outcomes were the pooled incidence rate ratio (IRR) for estimating the risk of subsequent infection. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies. Statistical analyses were conducted using the R programming language 4.0.2. We identified 19 eligible studies including more than 3.5 million individuals without the history of COVID-19 vaccination. The efficacy of naturally acquired antibodies against reinfection was estimated at 84% (pooled IRR = 0.16, 95% CI: 0.14-0.18), with higher efficacy against symptomatic COVID-19 cases (pooled IRR = 0.09, 95% CI = 0.07-0.12) than asymptomatic infection (pooled IRR = 0.28, 95% CI = 0.14-0.54). In the subgroup analyses, the pooled IRRs of COVID-19 infection in health care workers (HCWs) and the general population were 0.22 (95% CI = 0.16-0.31) and 0.14 (95% CI = 0.12-0.17), respectively, with a significant difference (P = 0.02), and those in older (over 60 years) and younger (under 60 years) populations were 0.26 (95% CI = 0.15–0.48) and 0.16 (95% CI = 0.14-0.19), respectively. The risk of subsequent infection in the seropositive population appeared to increase slowly over time. In conclusion, naturally acquired antibodies against SARS-CoV-2 can significantly reduce the risk of subsequent infection, with a protection efficacy of 84%. Registration number: CRD42021286222
Collapse
Affiliation(s)
- Qi Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Kongxin Zhu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xiaohui Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Chunlan Zhuang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xingcheng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Yue Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xingmei Yao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Jiali Quan
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Hongyan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Shoujie Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Yingying Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Ting Wu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Jun Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Ningshao Xia
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China.,The Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen City, Fujian Province, People's Republic of China
| |
Collapse
|
4
|
Liu F, Ma Z, Wang Z, Xie S. Trade-Off between COVID-19 Pandemic Prevention and Control and Economic Stimulus. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13956. [PMID: 36360836 PMCID: PMC9653931 DOI: 10.3390/ijerph192113956] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 10/16/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has posed a severe threat to public health and economic activity. Governments all around the world have taken positive measures to, on the one hand, contain the epidemic spread and, on the other hand, stimulate the economy. Without question, tightened anti-epidemic policy measures restrain people's mobility and deteriorate the levels of social and economic activity. Meanwhile, loose policy measures bring little harm to the economy temporarily but could accelerate the transmission of the virus and ultimately wreck social and economic development. Therefore, these two kinds of governmental decision-making behaviors usually conflict with each other. With the purpose of realizing optimal socio-economic benefit over the full duration of the epidemic and to provide a helpful suggestion for the government, a trade-off is explored in this paper between the prevention and control of the epidemic, and economic stimulus. First, the susceptible-infectious-recovered (SIR) model is introduced to simulate the epidemic dynamics. Second, a state equation is constructed to describe the system state variable-the level of socio-economic activity dominated by two control variables. Specifically, these two variables are the strengths of the measures taken for pandemic prevention and control, and economic stimulus. Then, the objective function used to maximize the total socio-economic benefit over the epidemic's duration is defined, and an optimal control problem is developed. The statistical data of the COVID-19 epidemic in Wuhan are used to validate the SIR model, and a COVID-19 epidemic scenario is used to evaluate the proposed method. The solution is discussed in both static and dynamic strategies, according to the knowledge of the epidemic's duration. In the static strategy, two scenarios with different strengths (in terms of anti-epidemic and economic stimulus measures) are analyzed and compared. In the dynamic strategy, two global optimization algorithms, including the dynamic programming (DP) and Pontryagin's minimum principle (PMP), respectively, are used to acquire the solutions. Moreover, a sensitivity analysis of model parameters is conducted. The results demonstrate that the static strategy, which is independent of the epidemic's duration and can be easily solved, is capable of finding the optimal strengths of both policy measures. Meanwhile, the dynamic strategy, which generates global optimal trajectories of the control variables, can provide the path that leads to attaining the optimal total socio-economic benefit. The results reveal that the optimal total socio-economic benefit of the dynamic strategy is slightly higher than that of the static strategy.
Collapse
Affiliation(s)
- Fangfang Liu
- School of Marxism, Chang’an University, Xi’an 710064, China
| | - Zheng Ma
- School of Automobile, Chang’an University, Xi’an 710064, China
| | - Ziqing Wang
- NIT-O2S, UTBM, University Bourgogne Franche-Comté, 91110 Belfort, France
| | - Shaobo Xie
- School of Automobile, Chang’an University, Xi’an 710064, China
| |
Collapse
|
5
|
Bai J, Wang X, Wang J. An epidemic-economic model for COVID-19. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:9658-9696. [PMID: 35942777 PMCID: PMC9373439 DOI: 10.3934/mbe.2022449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In this paper, we propose a new mathematical model to study the epidemic and economic consequences of COVID-19, with a focus on the interaction between the disease transmission, the pandemic management, and the economic growth. We consider both the symptomatic and asymptomatic infections and incorporate the effectiveness of disease control into the respective transmission rates. Meanwhile, the progression of the pandemic and the evolution of the susceptible, infectious and recovered population groups directly impact the mitigation and economic development levels. We fit this model to the reported COVID-19 cases and unemployment rates in the US state of Tennessee, as a demonstration of a real-world application of the modeling framework.
Collapse
Affiliation(s)
- Jie Bai
- School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China
| | - Xiunan Wang
- Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA
| | - Jin Wang
- Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA
| |
Collapse
|
6
|
Jairoun AA, Al hemyari SS, Abdulla NM, Shahwan M, Hashim Jaber Bilal F, AL-Tamimi SK, Jairoun M, Zyoud SH, Kurdi A, Godman B. Acceptability and Willingness of UAE Residents to Use OTC Vending Machines to Deliver Self-Testing Kits for COVID-19 and the Implications. J Multidiscip Healthc 2022; 15:1759-1770. [PMID: 36039076 PMCID: PMC9419902 DOI: 10.2147/jmdh.s370441] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/04/2022] [Indexed: 11/23/2022] Open
Abstract
PURPOSE Self-testing kits for SARS-CoV-2 appear effective, practical, safe and reliable as well as helping patients with mild-to-moderate symptoms to be successfully managed at home without going to hospital. As a result, ease pressures on hospitals. OTC vending machines offer the potential for SARS-CoV-2 self-testing kits alongside making available OTC treatments to alleviate the symptoms of COVID-19. As a result, providing confidentiality alongside ease of use in case people do not want their status broad casted. Consequently, there was a need to assess the acceptability and willingness regarding the availability of OTC vending machines to dispense self-testing kits for SARS-CoV-2 among UAE residents to provide future direction. PATIENTS AND METHODS A cross-sectional survey using a designed questionnaire was based on previous research and expert input and pilot tested. All items in the final questionnaire were seen as acceptable with a satisfactory content validity. A purposive sampling strategy was used in the principal study by primarily sending a link to the questionnaire to UAE universities via Facebook and WhatsApp. RESULTS A total of 876 respondents participated in the study and completed the whole questionnaire. Most participants were female (63%), Arabic origin (42%) and holding a bachelor's degree (84.5%). There was high acceptability and willingness to use self-testing kits (87.2%), with 88.6% of respondents believing OTC vending machines would be beneficial for patients with actual or suspected SARS-CoV-2. Gender, nationality, educational level, employment status, having relatives infected with SARS-CoV-2 and being vaccinated were significantly associated with attitudes towards the self-testing kits. Recognised barriers include their potential costs, ease of access and help for those who cannot read the instructions. CONCLUSION Overall, there was high acceptability and willingness to use OTC vending machines to deliver self-testing kits for SARS-CoV-2 among the surveyed participants. Key barriers will need to be addressed to enhance their use.
Collapse
Affiliation(s)
- Ammar Abdulrahman Jairoun
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Pulau Pinang, Gelugor, 11800, Malaysia
- Health and Safety Department, Dubai Municipality, Dubai, United Arab Emirates
- Correspondence: Ammar Abdulrahman Jairoun, Moyad Shahwan, Tel +971558099957; +97106 705 6249, Email ;
| | - Sabaa Saleh Al hemyari
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Pulau Pinang, Gelugor, 11800, Malaysia
- Pharmacy Department, Emirates Health Services, Dubai, United Arab Emirates
| | | | - Moyad Shahwan
- College of Pharmacy and Health Sciences, Ajman University, Ajman, 346, United Arab Emirates
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates
| | - Farah Hashim Jaber Bilal
- Anesthesiology Department, Saint Georges Hospital, Beirut, Lebanon
- Valiant Hospital, Anesthesiology Department, Dubai, United Arab Emirates
| | | | - Maimona Jairoun
- College of Pharmacy and Health Sciences, Ajman University, Ajman, 346, United Arab Emirates
| | - Samer H Zyoud
- Nonlinear Dynamics Research Center (NDRC), Ajman University, Ajman, United Arab Emirates
| | - Amanj Kurdi
- Department of Pharmacoepidemiology, Strathclyde Institute of Pharmacy and Biomedical Science (SIPBS), University of Strathclyde, Glasgow, UK
- Department of Pharmacology and Toxicology, College of Pharmacy, Hawler Medical University, Erbil, Kurdistan Region Government, Iraq
- Center of Research and Strategic Studies, Lebanese French University, Erbil, Kurdistan Region Government, Iraq
- Division of Public Health Pharmacy and Management, School of Pharmacy, Sefako Makgatho Health Sciences University, Pretoria, South Africa
| | - Brian Godman
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates
- Department of Pharmacoepidemiology, Strathclyde Institute of Pharmacy and Biomedical Science (SIPBS), University of Strathclyde, Glasgow, UK
- Division of Public Health Pharmacy and Management, School of Pharmacy, Sefako Makgatho Health Sciences University, Pretoria, South Africa
| |
Collapse
|